A Guide for Spatial Omics Technologies: Innovation, Evaluation, and Application
This review presents a strategy‐centric framework for spatial omics technologies, organizing methods by how spatial information is experimentally encoded. It compares key performance trade‐offs across sequencing‐ and imaging‐based approaches, examines computational and practical limitations, and highlights biomedical applications. The analysis provides
Xiaofeng Wu +5 more
wiley +1 more source
Enhanced convolutional neural network accelerators with memory optimization for routing applications. [PDF]
Nallabelli SP, Sampath S.
europepmc +1 more source
Rapid Proteome‐Wide Discovery of Protein–Protein Interactions With ppIRIS
ppIRIS is a lightweight deep learning framework for proteome‐wide protein–protein interaction prediction directly from sequence. By fusing evolutionary and structural embeddings with a regularized Siamese architecture, ppIRIS achieves state‐of‐the‐art accuracy across species, enables minute‐scale screening, and reveals biologically validated bacterial ...
Luiz Felipe Piochi +4 more
wiley +1 more source
A scalable automated framework for multiply-accumulate unit design in high-performance computing applications. [PDF]
Venkatachalam A +2 more
europepmc +1 more source
A Fully Self‐Powered Digital Wearable System for the Auxiliary Treatment of Plantar Fasciitis
This study reports a system‐level fully self‐powered digital wearable system (FS‐DWS) for the auxiliary treatment of plantar fasciitis. By integrating arch support, energy harvesting, wearable sensing, and machine learning‐driven closed‐loop visualized feedback, the system enables effective plantar pressure reduction and self‐powered, real‐time plantar
Jiacheng Hou +10 more
wiley +1 more source
An energy efficient processor array and memory controller for accurate processing of convolutional neural network-based inference engines. [PDF]
Deepika S, Arunachalam V.
europepmc +1 more source
By combining ionic nonvolatile memories and transistors, this work proposes a compact synaptic unit to enable low‐precision neural network training. The design supports in situ weight quantization without extra programming and achieves accuracy comparable to ideal methods. This work obtains energy consumption advantage of 25.51× (ECRAM) and 4.84× (RRAM)
Zhen Yang +9 more
wiley +1 more source
Microcomb-enabled parallel self- calibration optical convolution streaming processor. [PDF]
Wang J +15 more
europepmc +1 more source
Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu +4 more
wiley +1 more source

